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    Siemens industrial edge
    Siemens' Rahul Garg predicts the impact of software-defined automation on industrial machine controls
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    Hand putting hexagon piece to fulfill the part of R&D icon for Research and Development
    Person's hand throws a computer hard disk into the trash bin
    Abstracted from hardware, software-defined platforms eliminate the need for single-source automation and can run on any compute device
    Docker platform word cloud 3d illustration
    Panoramic banner of man holds a collection of icons representing robotic process automation and software management
    Control, monitor and adjust processes through software interfaces, rather than rewiring or manually adjusting hardware
    Adult electrician builder engineer testing and screwing equipment in fuse box and repairing of modern electricity power station
    Decoupling of hardware and software allows for standardized automation applications to run across IT and OT hardware platforms
    Low Angle Shot In Fully Working Data Center IT Engineer Installs Hard Drive into Server Rack
    SDA emphasizes flexible, open-source, universal protocols and agnostic platforms
    Photo: ACS
    University of Wisconsin Engine Research Center. Photo: ACS
    ACS’ Roy Krans explains how SDA reduces reliance on proprietary hardware, enables remote monitoring and updates, speeds deployment and supports machine learning
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    As AI automates programming tasks, the industrial workforce’s specialized knowledge becomes essential in guiding intelligent systems
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    Siemens’ Xcelerator platform offers advanced monitoring and quality control features, especially in tool condition management
    System integrator Gray Solutions focuses on AI, robotics, machine vision, edge computing and digital twins
    Real-world data and a fully visualized platform allows engineering and operations to interpret the system state and motion